Search results for: automatic classification

Authors: Seongcheol Kwon, Jeongmin Kim, Kwang Ryel Ryu

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We assume an IoT-based smart-home environment where the on-off status of each of the electrical appliances including the room lights can be recognized in a real time by monitoring and analyzing the smart meter data. At any moment in such an environment, we can recognize what the household or the user is doing by referring to the status data of the appliances. In this paper, we focus on a smart-home service that is to activate a robot vacuum cleaner at right time by recognizing the user situation, which requires a situation-aware model that can distinguish the situations that allow vacuum cleaning (Yes) from those that do not (No). We learn as our candidate models a few classifiers such as naïve Bayes, decision tree, and logistic regression that can map the appliance-status data into Yes and No situations. Our training and test data are obtained from simulations of user behaviors, in which a sequence of user situations such as cooking, eating, dish washing, and so on is generated with the status of the relevant appliances changed in accordance with the situation changes. During the simulation, both the situation transition and the resulting appliance status are determined stochastically. To compare the performances of the aforementioned classifiers we obtain their learning curves for different types of users through simulations. The result of our empirical study reveals that naïve Bayes achieves a slightly better classification accuracy than the other compared classifiers.

Keywords: situation-awareness, smart home, IoT, machine learning, classifier

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Authors: Sanath Kumar Shetty, Sanya Sinha, K. Kamalakanth Shenoy

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The posterior reference for the ala tragal line is a cause of confusion, with different authors suggesting different locations as to the superior, middle or inferior part of the tragus. This study was conducted on 200 subjects to evaluate if any correlation exists between the variation of angulation of palatal throat form and the relative parallelism of occlusal plane to ala-tragal line at different tragal levels. A Custom made Occlusal Plane Analyzer was used to check the parallelism between the ala-tragal line and occlusal plane. A lateral cephalogram was shot for each subject to measure the angulation of the palatal throat form. Fisher’s exact test was used to evaluate the correlation between the angulation of the palatal throat form and the relative parallelism of occlusal plane to the ala tragal line. Also, a classification was formulated for the palatal throat form, based on confidence interval. From the results of the study, the inferior part, middle part and superior part of the tragus were seen as the reference points in 49.5%, 32% and 18.5% of the subjects respectively. Class I palatal throat form (41degree-50 degree), Class II palatal throat form (below 41 degree) and Class III palatal throat form (above 50 degree) were seen in 42%, 43% and 15% of the subjects respectively. It was also concluded that there is no significant correlation between the variation in the angulations of the palatal throat form and the relative parallelism of occlusal plane to the ala-tragal line.

Keywords: Ala-Tragal line, occlusal plane, palatal throat form, cephalometry

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Authors: Malik Muhammad Akhtar, Tanzeel Khan

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Various natural and anthropogenic factors are affecting recharge processes in urban areas due to intense urban expansion; land-use/landcover change (LULC) and climate considerably influence the ecosystem functions. In Quetta, a terrible transformation of LULC has occurred due to an increase in human population and rapid urbanization over the past years; according to the Pakistan Bureau of Statistics, the increase of population from 252,577 in 1972 to 2,275,699 in 2017 shows an abrupt rise which in turn has affected the aquifer recharge capability, vegetation, and precipitation at Quetta. This study focuses on the influence of population growth and LULC on groundwater table level by employing multi-temporal, multispectral satellite data during the selected years, i.e. 2014, 2017, and 2020. The results of land classification showed that barren land had shown a considerable decrease, whereas the urban area has increased over time from 152.4sq/km in 2014 to 195.5sq/km in 2017 to 283.3sq/km in 2020, whereas surface-water area coverage has increased since 2014 because of construction of few dams around the valley. Rapid urbanization stresses limited hydrology resources, and this needs to be addressed to conserve/sustain the resources through educating the local community, awareness regarding water use and climate change, and supporting artificial recharge of the aquifers.

Keywords: climate changes, urbanization, GIS, land use, Quetta, watershed

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Authors: Rehan Siddiqui, Brendan Quine

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The Radiance Enhancement (RE) and integrated absorption technique is applied to develop a synthetic model to determine the enhancement in radiance due to cloud scene and Shortwave upwelling Radiances (SHupR) by O2, H2O, CO2 and CH4. This new model is used to estimate the magnitude variation for RE and SHupR over spectral range of 900 nm to 1700 nm by varying surface altitude, mixing ratios and surface reflectivity. In this work, we employ satellite real observation of space orbiting Argus 1000 especially for O2, H2O, CO2 and CH4 together with synthetic model by using line by line GENSPECT radiative transfer model. All the radiative transfer simulations have been performed by varying over a different range of percentages of water vapor contents and carbon dioxide with the fixed concentration oxygen and methane. We calculate and compare both the synthetic and real measured observed data set of different week per pass of Argus flight. Results are found to be comparable for both approaches, after allowing for the differences with the real and synthetic technique. The methodology based on RE and SHupR of the space spectral data can be promising for the instant and reliable classification of the cloud scenes.

Keywords: radiance enhancement, radiative transfer, shortwave upwelling radiative flux, cloud reflectivity, greenhouse gases

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Authors: Wajid Mumtaz, Aamir Saeed Malik, Syed Saad Azhar Ali, Mohd Azhar Mohd Yasin

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In this paper, a technique based on electroencephalogram (EEG) analysis is presented, aiming for diagnosing major depressive disorder (MDD) among a potential population of MDD patients and healthy controls. EEG is recognized as a clinical modality during applications such as seizure diagnosis, index for anesthesia, detection of brain death or stroke. However, its usability for psychiatric illnesses such as MDD is less studied. Therefore, in this study, for the sake of diagnosis, 2 groups of study participants were recruited, 1) MDD patients, 2) healthy people as controls. EEG data acquired from both groups were analyzed involving inter-hemispheric asymmetry and composite permutation entropy index (CPEI). To automate the process, derived quantities from EEG were utilized as inputs to classifier such as logistic regression (LR) and support vector machine (SVM). The learning of these classification models was tested with a test dataset. Their learning efficiency is provided as accuracy of classifying MDD patients from controls, their sensitivities and specificities were reported, accordingly (LR =81.7 % and SVM =81.5 %). Based on the results, it is concluded that the derived measures are indicators for diagnosing MDD from a potential population of normal controls. In addition, the results motivate further exploring other measures for the same purpose.

Keywords: major depressive disorder, diagnosis based on EEG, EEG derived features, CPEI, inter-hemispheric asymmetry

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Authors: Shidrokh Goudarzi, Wan Haslina Hassan

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Heterogeneous wireless networks are converging towards an all-IP network as part of the so-called next-generation network. In this paradigm, different access technologies need to be interconnected; thus, vertical handovers or vertical handoffs are necessary for seamless mobility. In this paper, we conduct a review of existing vertical handover decision-making mechanisms that aim to provide ubiquitous connectivity to mobile users. To offer a systematic comparison, we categorize these vertical handover measurement and decision structures based on their respective methodology and parameters. Subsequently, we analyze several vertical handover approaches in the literature and compare them according to their advantages and weaknesses. The paper compares the algorithms based on the network selection methods, complexity of the technologies used and efficiency in order to introduce our vertical handover decision framework. We find that vertical handovers on heterogeneous wireless networks suffer from the lack of a standard and efficient method to satisfy both user and network quality of service requirements at different levels including architectural, decision-making and protocols. Also, the consolidation of network terminal, cross-layer information, multi packet casting and intelligent network selection algorithm appears to be an optimum solution for achieving seamless service continuity in order to facilitate seamless connectivity.

Keywords: heterogeneous wireless networks, vertical handovers, vertical handover metric, decision-making algorithms

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Authors: V. Emery David Jr., J. Wenchao, D. Mmereki, Y. John, F. Heriniaina

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Healthcare waste management continues to present an array of challenges for developing countries, and Liberia is of no exception. There is insufficient information available regarding the generation, handling, and disposal of health care waste. This face serves as an impediment to healthcare management schemes. The specific objective of this study is to present an evaluation of the current health care management practices in Liberia. It also presented procedures, techniques used, methods of handling, transportation, and disposal methods of wastes as well as the quantity and composition of health care waste. This study was conducted as an investigative case study, covering three different health care facilities; a hospital, a health center, and a clinic in Monrovia, Montserrado County. The average waste generation was found to be 0-7kg per day at the clinic and health center and 8-15kg per/day at the hospital. The composition of the waste includes hazardous and non-hazardous waste i.e. plastic, papers, sharps, and pathological elements etc. Nevertheless, the investigation showed that the healthcare waste generated by the surveyed healthcare facilities were not properly handled because of insufficient guidelines for separate collection, and classification, and adequate methods for storage and proper disposal of generated wastes. This therefore indicates that there is a need for improvement within the healthcare waste management system to improve the existing situation.

Keywords: disposal, healthcare waste, management, Montserrado County, Monrovia

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Authors: Renate Gericke, Carol Long

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Despite the robust empirical support of attachment, advancement in the description and conceptualization of attachment has been slow and has not significantly advanced beyond the identification of attachment security or type (namely, secure, avoidant, ambivalent and disorganized). This has continued despite papers arguing for theoretical refinement in the classification of attachment presentations. For thinking and practice to advance, it is critically important that these categories and their assessment be interrogated in different contexts and across developmental age. To achieve this, a quantitative design was used with descriptive and inferential statistics, and general linear models were employed to analyze the data. The Attachment Story Completion Test (ASCT) was administered to 105 children between the ages of eight and twelve from socio-economically deprived contexts with high exposure to trauma. A staggering 93% of the children had insecure attachments (specifically, avoidant 37%, disorganized 34% and ambivalent 22%) and attachment was more complex than currently conceptualized in the attachment literature. Primary attachment did not only present as one of four discreet categories, but 70% of the sample had a complex attachment with more than one type of maternal attachment style. Attachment intensity also varied along a continuum (between 1 and 5). The findings have implications for a) research that has not considered the potential complexity of attachment or attachment intensity, b) policy to more actively support mother-infant dyads, particularly in high-risk contexts and c) question the applicability of a western conceptualization of a primary maternal attachment figure in non-western collectivist societies.

Keywords: attachment, children at risk, middle childhood, non-western context

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Authors: N. K. Caecar Pratiwi, Yunendah Nur Fuadah, Rita Magdalena, R. D. Atmaja, Sofia Saidah, Ocky Tiaramukti

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Colon cancer or colorectal cancer is a type of cancer that attacks the last part of the human digestive system. Lymphoma and carcinoma are types of cancer that attack human’s colon. Colon cancer causes deaths about half a million people every year. In Indonesia, colon cancer is the third largest cancer case for women and second in men. Unhealthy lifestyles such as minimum consumption of fiber, rarely exercising and lack of awareness for early detection are factors that cause high cases of colon cancer. The aim of this project is to produce a system that can detect and classify images into type of colon cancer lymphoma, carcinoma, or normal. The designed system used 198 data colon cancer tissue pathology, consist of 66 images for Lymphoma cancer, 66 images for carcinoma cancer and 66 for normal / healthy colon condition. This system will classify colon cancer starting from image preprocessing, feature extraction using Principal Component Analysis (PCA) and classification using K-Nearest Neighbor (K-NN) method. Several stages in preprocessing are resize, convert RGB image to grayscale, edge detection and last, histogram equalization. Tests will be done by trying some K-NN input parameter setting. The result of this project is an image processing system that can detect and classify the type of colon cancer with high accuracy and low computation time.

Keywords: carcinoma, colorectal cancer, k-nearest neighbor, lymphoma, principle component analysis

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Authors: Angelica S. Valeriani, Lorenzo Biasiolo

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In recent years, the scale of the impact of climate change and its related side effects has become ever more massive and devastating. Sustainable Development Goals (SDGs), promoted by United Nations, aim to front issues related to climate change, among others. In particular, the project CROWD4SDG focuses on a bunch of SDGs since it promotes environmental activities and climate-related issues. In this context, we developed a prototype of an application, under advanced development considering web design, that focuses on SDG 13 (SDG on climate action) by providing users with useful instruments to face environmental crises and climate-related disasters. Our prototype is thought and structured for both web and mobile development. The main goal of the application, POLI4SDG, is to help users to get through emergency services. To this extent, an organized overview and classification prove to be very effective and helpful to people in need. A careful analysis of data related to environmental crises prompted us to integrate the user contribution, i.e., exploiting a core principle of Citizen Science, into the realization of a public catalog, available for consulting and organized according to typology and specific features. In addition, gender equality and opportunity features are considered in the prototype in order to allow women, often the most vulnerable category, to have direct support. The overall description of the application functionalities is detailed. Moreover, the implementation features and properties of the prototype are discussed.

Keywords: crowdsourcing, social media, SDG, climate change, natural disasters, gender equality

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Authors: Kimberly McCabe

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The trafficking of women and children for abuse and exploitation is not a new problem under the umbrella of human trafficking; however, over the last decade, the problem has attracted increased attention from international governments and non-profits attempting to reduce victimization and provide services for survivors. Research on human trafficking suggests that the trafficking of human beings is, largely, a symptom of poverty. As the trafficking of human beings may be viewed as a response to the demand for people for various forms of exploitation, a product of poverty, and a consequence of the subordinate positions of women and children in society, it reaches beyond randomized victimization. Hence, human trafficking, and especially the trafficking of women and children, goes beyond the realm of poorness. Therefore, to begin to understand the reasons for the existence of human trafficking, one must identify and consider not only the immediate causes but also those underlying structural determinants that facilitate this form of victimization. Specifically, one must acknowledge the economic, social, and cultural factors that support human trafficking. This research attempts to study human trafficking at the country level by focusing on economic, social, and cultural characteristics. This study focuses on inequality and, in particular, gender inequality as related to legislative attempts to address human trafficking. Within the design of this project is the use of the US State Department’s tier classification system for Trafficking in Persons (TIP) and the USA CIA Fact Sheet of country characteristics for over 150 countries in an attempt to model legal outcomes as related to human trafficking. Results of this research demonstrate the significance of characteristics beyond poverty as related to country-level responses to human trafficking.

Keywords: child trafficking, gender inequality, human trafficking, inequality

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Authors: S. alireza Mirghasemi, Shervin Rashidinia, Mohammadsaleh Sadeghi, Mohsen Talebizadeh, Narges Rahimi Gabaran, S. Shahin Eftekhari, Sara Shahmoradi

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Purpose: There are various pin-in-plaster methods for treating distal radius fractures. This study is meant to introduce a modified technique of pin-in-plaster. Materials and methods: Fifty-four patients with distal radius fractures were followed up for one year. Patients were excluded if they had type B fractures according to AO classification, multiple injuries or pathological fractures, and were treated more than 7 days after injury. Range of motion and functional results were evaluated. Radiographic parameters including radial inclination, tilt, and height, were measured preoperatively and postoperatively. Results: The average radial tilt was 10.6° and radial height was 10.2 mm at the sixth month postoperatively. Three cases of pin tract infection were recorded, who were treated totally with oral antibiotics. There was no case of pin loosening. Of total 73 patients underwent surgery, three cases of radial nerve irritation were recorded at the time of cast removal. All of them resolved at the 6th month follow up. No median nerve compression and carpal tunnel syndrome have found. We also had no case of tendon injury. Conclusion: Our modified technique is effective to restore anatomic congruity and maintain reduction.

Keywords: distal radius fracture, percutaneous pinning, pin-in-plaster, modified method of pin-in-plaster, operative treatment

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Authors: Sandesh Achar

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Personalized advertising holds greater potential for higher conversion rates compared to generic advertisements. However, its widespread application in the retail industry faces challenges due to complex implementation processes. These complexities impede the swift adoption of personalized advertisement on a large scale. Personalized advertisement, being a data-driven approach, necessitates consumer-related data, adding to its complexity. This paper introduces an innovative data-driven decision-making framework, D3Advert, which personalizes advertisements by analyzing personalities using a BiLSTM network. The framework utilizes the Myers–Briggs Type Indicator (MBTI) dataset for development. The employed BiLSTM network, specifically designed and optimized for D3Advert, classifies user personalities into one of the sixteen MBTI categories based on their social media posts. The classification accuracy is 86.42%, with precision, recall, and F1-Score values of 85.11%, 84.14%, and 83.89%, respectively. The D3Advert framework personalizes advertisements based on these personality classifications. Experimental implementation and performance analysis of D3Advert demonstrate a 40% improvement in impressions. D3Advert’s innovative and straightforward approach has the potential to transform personalized advertising and foster widespread personalized advertisement adoption in marketing.

Keywords: personalized advertisement, deep Learning, MBTI dataset, BiLSTM network, NLP.

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Authors: Taki Eddine Seghier, Mohd Hamdan Ahmad, Yaik-Wah Lim, Samuel Opeyemi Williams

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The assessment of building sustainability to achieve a specific green benchmark and the preparation of the required documents in order to receive a green building certification, both are considered as major challenging tasks for green building design team. However, this labor and time-consuming process can take advantage of the available Building Information Modeling (BIM) features such as material take-off and scheduling. Furthermore, the workflow can be automated in order to track potentially achievable credit points and provide rating feedback for several design options by using integrated Visual Programing (VP) to handle the stored parameters within the BIM model. Hence, this study proposes a BIM-based tool that uses Green Building Index (GBI) rating system requirements as a unique input case to evaluate the building sustainability in the design stage of the building project life cycle. The tool covers two key models for data extraction, firstly, a model for data extraction, calculation and the classification of achievable credit points in a green template, secondly, a model for the generation of the required documents for green building certification. The tool was validated on a BIM model of residential building and it serves as proof of concept that building sustainability assessment of GBI certification can be automatically evaluated and documented through BIM.

Keywords: green building rating system, GBRS, building information modeling, BIM, visual programming, VP, sustainability assessment

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Authors: Ferdinando Montemari, Antonio Vitale, Nicola Genito, Giovanni Cuciniello

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The introduction of tilt-rotor aircraft into the existing civilian air transportation system will provide beneficial effects due to tilt-rotor capability to combine the characteristics of a helicopter and a fixed-wing aircraft into one vehicle. The disposability of reliable tilt-rotor simulation models supports the development of such vehicle. Indeed, simulation models are required to design automatic control systems that increase safety, reduce pilot's workload and stress, and ensure the optimal aircraft configuration with respect to flight envelope limits, especially during the most critical flight phases such as conversion from helicopter to aircraft mode and vice versa. This article presents a process to build a simplified tilt-rotor simulation model, derived from the analysis of flight data. The model aims to reproduce the complex dynamics of tilt-rotor during the in-flight conversion phase. It uses a set of scheduled linear transfer functions to relate the autopilot reference inputs to the most relevant rigid body state variables. The model also computes information about the rotor flapping dynamics, which are useful to evaluate the aircraft control margin in terms of rotor collective and cyclic commands. The rotor flapping model is derived through a mixed theoretical-empirical approach, which includes physical analytical equations (applicable to helicopter configuration) and parametric corrective functions. The latter are introduced to best fit the actual rotor behavior and balance the differences existing between helicopter and tilt-rotor during flight. Time-domain system identification from flight data is exploited to optimize the model structure and to estimate the model parameters. The presented model-building process was applied to simulated flight data of the ERICA Tilt-Rotor, generated by using a high fidelity simulation model implemented in FlightLab environment. The validation of the obtained model was very satisfying, confirming the validity of the proposed approach.

Keywords: flapping dynamics, flight dynamics, system identification, tilt-rotor modeling and simulation

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Authors: Jasim Uddin, Rod Smith, Malcolm Gillies

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Surface irrigation is the most popular irrigation method all over the world. However, two issues: low efficiency and huge labour involvement concern irrigators due to scarcity in recent years. To address these issues, a smart automated furrow is conceptualised that can be operated using digital devices like smartphone, iPad or computer and a preliminary evaluation was conducted in this study. The smart automated system is the integration of commercially available software and hardware. It includes real-time surface irrigation optimisation software (SISCO) and Rubicon Water’s surface irrigation automation hardware and software. The automated system consists of automatic water delivery system with 300 mm flexible pipes attached to both sides of a remotely controlled valve to operate the irrigation. A water level sensor to obtain the real-time inflow rate from the measured head in the channel, advance sensors to measure the advance time to particular points of an irrigated field, a solar-powered telemetry system including a base station to communicate all the field sensors with the main server. On the basis of field data, the software (SISCO) is optimised the ongoing irrigation and determine the optimum cut-off for particular irrigation and send this information to the control valve to stop the irrigation in a particular (cut-off) time. The preliminary evaluation shows that the automated surface irrigation worked reasonably well without manual intervention. The evaluation of farmers managed irrigation events show the potentials to save a significant amount of water and labour. A substantial amount of economic and social benefits are expected in rural industries by adopting this system. The future outcome of this work would be a fully tested commercial adaptive real-time furrow irrigation system able to compete with the pressurised alternative of centre pivot or lateral move machines on capital cost, water and labour savings but without the massive energy costs.

Keywords: furrow irrigation, smart automation, infiltration, SISCO, real-time irrigation, adoptive control

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Authors: Elham Allahmoradi, Bahman Allahmoradi, Ali Bonyadi Naeini

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Complex systems have many aspects. A variety of methods have been developed to analyze these systems. The most efficient of these methods should not only be simple, but also provide useful and comprehensive information about many aspects of the system. Matrix methods are considered the most commonly methods used to analyze and design systems. Each matrix method can examine a particular aspect of the system. If these methods are combined, managers can access to more comprehensive and broader information about the system. This study was conducted in four steps. In the first step, a process model of a real project has been extracted through IDEF3. In the second step, activity levels have been attained by writing a process model in the form of a design structure matrix (DSM) and sorting it through triangulation algorithm (TA). In the third step, sub-processes have been obtained by writing the process model in the form of an interface structure matrix (ISM) and clustering it through cluster identification algorithm (CIA). In the fourth step, a mixed model has been developed to provide a unified picture of the project structure through the simultaneous presentation of activities and sub-processes. Finally, the paper is completed with a conclusion.

Keywords: integrated definition for process description capture (IDEF3) method, design structure matrix (DSM), interface structure matrix (ism), mixed matrix model, activity level, sub-process

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Authors: Kartik Thakore, Anna-Roza Tamas, Adam Cole

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The world health organization (WHO) reports that by 2030 more than 23.7 million deaths annually will be caused by Cardiovascular Diseases (CVDs); with a 2008 economic impact of $3.76 T. Metabolic syndrome is a disorder of multiple metabolic risk factors strongly indicated in the development of cardiovascular diseases. Guided lifestyle intervention driven by live coaching has been shown to have a positive impact on metabolic risk factors. Individuals’ path to improved (decreased) metabolic risk factors are driven by personal motivation and personalized messages delivered by coaches and augmented by technology. Using interactions captured between 400 individuals and 3 coaches over a program period of 500 days, a preliminary model was designed. A novel real time event tracking system was created to track and classify clients based on their genetic profile, baseline questionnaires and usage of a mobile application with live coaching sessions. Classification of clients and coaches was done using a support vector machines application build on Apache Spark, Stanford Natural Language Processing Library (SNLPL) and decision-modeling.

Keywords: guided lifestyle intervention, metabolic risk factors, personal coaching, support vector machines application, Apache Spark, natural language processing

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Authors: Jie Liu, Wei Wei, Chun-Ping Chang

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Using a sample of 110 countries over the period 1984-2013, this paper examines the impacts of country risks on choosing a specific exchange rate regime (first by utilizing the Levy-Yeyati and Sturzenegger de facto classification and then robusting it by the IMF de jure measurement) relative to other regimes via the panel multinomial logit approach. Empirical findings are as follows. First, in the full samples case we provide evidence that government is more likely to implement a flexible regime, but less likely to adopt a fixed regime, under a low level of composite and financial risk. Second, we find that Eurozone countries are more likely to choose a fixed exchange rate regime with a decrease in the level of country risk and favor a flexible regime in response to a shock from an increase of risk, which is opposite to non-Eurozone countries. Third, we note that high-risk countries are more likely to choose a fixed regime with a low level of composite and political risk in the government, but do not adjust the exchange rate regime as a shock absorber when facing economic and financial risks. It is interesting to see that those countries with relatively low risk display almost opposite results versus high-risk economies. Overall, we believe that it is critically important to account for political economy variables in a government’s exchange rate policy decisions, especially for country risks. All results are robust to the panel ordered probit model.

Keywords: country risk, political economy, exchange rate regimes, shock absorber

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Authors: Y. Sarı Nayim, B. N. Nayim

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This research proposal includes the defining and evaluation of the semi-natural and cultural ecosystems at Bartın University main campus in Turkey in terms of landscape mosaics. The ecosystem mosaic of the main campus was divided into zones based on ecological classification technique. Based on the results from the study, it was found that 6 different ecosystem mosaics should be used as a base in the planning and design of the existing and future landscape planning of Kutlubeyyazıcılar campus. The first landscape zone involves the 'social areas'. These areas include yards, dining areas, recreational areas and lawn areas. The second landscape zone is 'main vehicle and pedestrian areas'. These areas include vehicle access to the campus landscape, moving in the campus with vehicles, parking and pedestrian walk ways. The third zone is 'landscape areas with high visual landscape quality'. These areas will be the places where attractive structural and plant landscape elements will be used. Fourth zone will be 'landscapes of building borders and their surroundings.' The fifth and important zone that should be survived in the future is 'Actual semi-natural forest and bush areas'. And the last zone is 'water landscape' which brings ecological value to landscape areas. While determining the most convenient areas in the planning and design of the campus, these landscape mosaics should be taken into consideration. This zoning will ensure that the campus landscape is protected and living spaces in the campus apart from the areas where human activities are carried out will be used properly.

Keywords: campus landscape planning and design, landscape ecology, landscape mosaics, Bartın

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Authors: Adam Chlapecka, Anna Kagstrom, Pavla Cermakova

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Background: Increasing educational attainment (EA) could decrease the occurrence of depression. We investigated the relationship between EA and depressive symptoms in older individuals across four European regions. Methods: We studied 108 315 Europeans (54 % women, median age 63 years old) from the Survey on Health, Ageing and Retirement in Europe assessing EA (7 educational levels based on ISCED classification); and depressive symptoms (≥ 4 points on EURO-D scale). Logistic regression estimated the association between EA and depressive symptoms, adjusting for sociodemographic and health-related factors; testing for sex/age/region and education interactions. Results: Higher EA was associated with lower odds of depressive symptoms, independent of sociodemographic and health-related factors. A threshold of the lowest odds of depressive symptoms was detected at the first stage of tertiary education (OR 0.60; 95% CI 0.55-0.65; p<0.001; relative to no education). Central and Eastern Europe showed the strongest association (OR for high vs. low education 0.37; 95% CI 0.33-0.40; p<0.001) and Scandinavia the weakest (OR for high vs. low education 0.69; 95% CI 0.60-0.80; p<0.001). The association was strongest amongst younger individuals. There was a sex and education interaction only within Central and Eastern Europe. Conclusion: The level of EA is reflected in later-life depressive symptoms, suggesting that supporting individuals in achieving EA, and considering those with lower EA at increased risk for depression, could lead to the decreased burden of depression across the life course. Further educational support in Central and Eastern Europe may decrease the higher burden of depressive symptoms in women.

Keywords: depression, education, epidemiology, Europe

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Authors: Svetlana Ignatjeva, Jelena Slesareva

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The aim of the study is development and adaptation of the method to analyze and quantify the indicators characterizing the relationship between a company and its employees. Diagnostics of such indicators is one of the most complex and actual issues in psychology of labour. The offered method is based on the questionnaire; its indicators reflect cognitive, affective and connotative components of socio-psychological attitude of employees to be as efficient as possible in their professional activities. This approach allows measure not only the selected factors but also such parameters as cognitive and behavioural dissonances. Adaptation of the questionnaire includes factor structure analysis and suitability analysis of phenomena indicators measured in terms of internal consistency of individual factors. Structural validity of the questionnaire was tested by exploratory factor analysis. Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. Factor analysis allows reduce dimension of the phenomena moving from the indicators to aggregative indexes and latent variables. Aggregative indexes are obtained as the sum of relevant indicators followed by standardization. The coefficient Cronbach's Alpha was used to assess the reliability-consistency of the questionnaire items. The two-step cluster analysis in the space of allocated factors allows classify employees according to their attitude to work in the company. The results of psychometric testing indicate possibility of using the developed technique for the analysis of employees’ attitude towards their work in companies and development of recommendations on their optimization.

Keywords: involved in the organization, loyalty, organizations, method

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Authors: Zahra Kazemi Saleh, Bénédicte Poulin-Charronnat, Annie Vinter

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This study examines the effects of aging on visual statistical learning, using eye-tracking techniques to investigate this cognitive phenomenon. Visual statistical learning is a fundamental brain function that enables the automatic and implicit recognition, processing, and internalization of environmental patterns over time. Some previous research has suggested the robustness of this learning mechanism throughout the aging process, underscoring its importance in the context of education and rehabilitation for the elderly. The study included three distinct groups of participants, including 21 young adults (Mage: 19.73), 20 young-old adults (Mage: 67.22), and 17 old-old adults (Mage: 79.34). Participants were exposed to a series of 12 arbitrary black shapes organized into 6 pairs, each with different spatial configurations and orientations (horizontal, vertical, and oblique). These pairs were not explicitly revealed to the participants, who were instructed to passively observe 144 grids presented sequentially on the screen for a total duration of 7 min. In the subsequent test phase, participants performed a two-alternative forced-choice task in which they had to identify the most familiar pair from 48 trials, each consisting of a base pair and a non-base pair. Behavioral analysis using t-tests revealed notable findings. The mean score for the first group was significantly above chance, indicating the presence of visual statistical learning. Similarly, the second group also performed significantly above chance, confirming the persistence of visual statistical learning in young-old adults. Conversely, the third group, consisting of old-old adults, showed a mean score that was not significantly above chance. This lack of statistical learning in the old-old adult group suggests a decline in this cognitive ability with age. Preliminary eye-tracking results showed a decrease in the number and duration of fixations during the exposure phase for all groups. The main difference was that older participants focused more often on empty cases than younger participants, likely due to a decline in the ability to ignore irrelevant information, resulting in a decrease in statistical learning performance.

Keywords: aging, eye tracking, implicit learning, visual statistical learning

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Authors: N. A. P. Camaforte, P. M. P. Vareda, L. L. Saldanha, A. L. Dokkedal, J. M. Rezende-Neto, M. R. Senger, F. P. Silva-Jr, J. R. Bosqueiro

Abstract:

Diabetes mellitus is a disease characterized by deficiency of insulin secretion and/or action which results in hyperglycemia. Nowadays, acarbose is a medicine used by diabetic people to inhibit alpha-glucosidases leading to the decreasing of post-feeding glycaemia, but with low effectiveness and many side effects. Medicinal plants have been used for the treatment of many diseases including diabetes and their action occurs through the modulation of insulin-depending processes, pancreas regeneration or inhibiting glucose absorption by the intestine. Previous studies in our laboratory showed that the treatment using two crude extracts of plants from Brazilian cerrado was able to decrease fasting blood glucose and improve glucose tolerance in streptozotocin-diabetic mice. Because of this and the importance of the search for new alternatives to decrease the hyperglycemia, we decided to evaluate the inhibitory action of two plants from Brazilian cerrado - B.H. and Myrcia bella. The enzymatic assay was performed in 50 µL of final volume using pancreatic α-amylase and maltase together with theirs commercial substrates. The inhibition potency (IC50) was determined by the incubation of eight different concentrations of both extracts and the enzymes for 5 minutes at 37ºC. After, the substrate was added to start the reaction. Glucosidases assay was evaluated measuring the quantity of p-nitrophenol in 405 nmin 384 wells automatic reader. The in vitro assay with the extracts of B.H. and M. bella showed an IC50 of 28,04µg/mL and 16,93 µg/mL for α-amilase, and 43,01µg/mL and 17 µg/mL for maltase, respectively. M. bella extract showed a higher inhibitory activity for those enzymes than B.H. extract. The crude extracts tested showed a higher inhibition rate to α-amylase, but were less effective against maltase in comparison to acarbose (IC50 36µg/mL and 9 µg/mL, respectively). In conclusion, the crude extract of B.H. and M. bella showed a potent inhibitory effect against α-amylase and showed promising results to the possible development of new medicines to treat diabetes with less or even without side effects.

Keywords: alfa-glucosidases, diabetes mellitus, glycaemia, medicinal plants

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Authors: Khadija Refouh

Abstract:

Culture bound-expressions have been a bottleneck for Natural Language Processing (NLP) and comprehension, especially in the case of machine translation (MT). In the last decade, the field of machine translation has greatly advanced. Neural machine translation NMT has recently achieved considerable development in the quality of translation that outperformed previous traditional translation systems in many language pairs. Neural machine translation NMT is an Artificial Intelligence AI and deep neural networks applied to language processing. Despite this development, there remain some serious challenges that face neural machine translation NMT when translating culture bounded-expressions, especially for low resources language pairs such as Arabic-English and Arabic-French, which is not the case with well-established language pairs such as English-French. Machine translation of opaque idioms from English into French are likely to be more accurate than translating them from English into Arabic. For example, Google Translate Application translated the sentence “What a bad weather! It runs cats and dogs.” to “يا له من طقس سيء! تمطر القطط والكلاب” into the target language Arabic which is an inaccurate literal translation. The translation of the same sentence into the target language French was “Quel mauvais temps! Il pleut des cordes.” where Google Translate Application used the accurate French corresponding idioms. This paper aims to perform NMT experiments towards better translation of opaque idioms using high quality clean multilingual corpus. This Corpus will be collected analytically from human generated idiom translation. AutoML translation, a Google Neural Machine Translation Platform, is used as a custom translation model to improve the translation of opaque idioms. The automatic evaluation of the custom model will be compared to the Google NMT using Bilingual Evaluation Understudy Score BLEU. BLEU is an algorithm for evaluating the quality of text which has been machine-translated from one natural language to another. Human evaluation is integrated to test the reliability of the Blue Score. The researcher will examine syntactical, lexical, and semantic features using Halliday's functional theory.

Keywords: multilingual corpora, natural language processing (NLP), neural machine translation (NMT), opaque idioms

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Authors: Rodolfo Lorbieski, Silvia Modesto Nassar

Abstract:

Many supervised machine learning tasks require decision making across numerous different classes. Multi-class classification has several applications, such as face recognition, text recognition and medical diagnostics. The objective of this article is to analyze an adapted method of Stacking in multi-class problems, which combines ensembles within the ensemble itself. For this purpose, a training similar to Stacking was used, but with three levels, where the final decision-maker (level 2) performs its training by combining outputs from the tree-based pair of meta-classifiers (level 1) from Bayesian families. These are in turn trained by pairs of base classifiers (level 0) of the same family. This strategy seeks to promote diversity among the ensembles forming the meta-classifier level 2. Three performance measures were used: (1) accuracy, (2) area under the ROC curve, and (3) time for three factors: (a) datasets, (b) experiments and (c) levels. To compare the factors, ANOVA three-way test was executed for each performance measure, considering 5 datasets by 25 experiments by 3 levels. A triple interaction between factors was observed only in time. The accuracy and area under the ROC curve presented similar results, showing a double interaction between level and experiment, as well as for the dataset factor. It was concluded that level 2 had an average performance above the other levels and that the proposed method is especially efficient for multi-class problems when compared to binary problems.

Keywords: stacking, multi-layers, ensemble, multi-class

Procedia PDF Downloads 266

Authors: D. Szinay, O. Perski, A. Jones, T. Chadborn, J. Brown, F. Naughton

Abstract:

Background: The uptake of health and wellbeing smartphone apps is largely influenced by popularity indicators (e.g., rankings), rather than evidence-based content. Rapid disengagement is common. This study aims to explore how and why potential users 1) select and 2) engage with such apps, and 3) how increased engagement could be promoted. Methods: Semi-structured interviews and a think-aloud approach were used to allow participants to verbalise their thoughts whilst searching for a health or wellbeing app online, followed by a guided search in the UK National Health Service (NHS) 'Apps Library' and Public Health England’s (PHE) 'One You' website. Recruitment took place between June and August 2019. Adults interested in using an app for behaviour change were recruited through social media. Data were analysed using the framework approach. The analysis is both inductive and deductive, with the coding framework being informed by the Theoretical Domains Framework. The results are further mapped onto the COM-B (Capability, Opportunity, Motivation - Behaviour) model. The study protocol is registered on the Open Science Framework (https://osf.io/jrkd3/). Results: The following targets were identified as playing a key role in increasing the uptake of and engagement with health and wellbeing apps: 1) psychological capability (e.g., reduced cognitive load); 2) physical opportunity (e.g., low financial cost); 3) social opportunity (e.g., embedded social media); 4) automatic motivation (e.g., positive feedback). Participants believed that the promotion of evidence-based apps on NHS-related websites could be enhanced through active promotion on social media, adverts on the internet, and in general practitioner practices. Future Implications: These results can inform the development of interventions aiming to promote the uptake of and engagement with evidence-based health and wellbeing apps, a priority within the UK NHS Long Term Plan ('digital first'). The targets identified across the COM-B domains could help organisations that provide platforms for such apps to increase impact through better selection of apps.

Keywords: behaviour change, COM-B model, digital health, mhealth

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Authors: Sagri Sharma

Abstract:

Analysis of diseases integrating multi-factors increases the complexity of the problem and therefore, development of frameworks for the analysis of diseases is an issue that is currently a topic of intense research. Due to the inter-dependence of the various parameters, the use of traditional methodologies has not been very effective. Consequently, newer methodologies are being sought to deal with the problem. Supervised Learning Algorithms are commonly used for performing the prediction on previously unseen data. These algorithms are commonly used for applications in fields ranging from image analysis to protein structure and function prediction and they get trained using a known dataset to come up with a predictor model that generates reasonable predictions for the response to new data. Gene expression profiles generated by DNA analysis experiments can be quite complex since these experiments can involve hypotheses involving entire genomes. The application of well-known machine learning algorithm - Support Vector Machine - to analyze the expression levels of thousands of genes simultaneously in a timely, automated and cost effective way is thus used. The objectives to undertake the presented work are development of a methodology to identify genes relevant to Hepatocellular Carcinoma (HCC) from gene expression dataset utilizing supervised learning algorithms and statistical evaluations along with development of a predictive framework that can perform classification tasks on new, unseen data.

Keywords: artificial intelligence, biomarker, gene expression datasets, hepatocellular carcinoma, machine learning, supervised learning algorithms, support vector machine

Procedia PDF Downloads 426

Authors: Dhiraj Dolai, Rupayan Bhattacharya

Abstract:

In this study, a comparison of Range Of Motion (ROM) of middle and long-distance runners and swimmers has been made. The mobility of the various joints is essential for the quick movement of any sportsman. Knowledge of a ROM helps in preventing injuries, in repeating the movement, and in generating speed and power. ROM varies among individuals, and it is influenced by factors such as gender, age, and whether the motion is performed actively or passively. ROM for running and swimming, both performed with due consideration on speed, plays an important role. The time of generation of speed and mobility of the particular joints are very important for both kinds of athletes. The difficulties that happen during running and swimming in the direction of motion is changed. In this study, data were collected for a total of 102 subjects divided into three groups: control group (22), middle and long-distance runners (40), and swimmers (40), and their ages are between 12 to 18 years. The swimmers have higher ROM in shoulder joint flexion, extension, abduction, and adduction movement. Middle and long-distance runners have significantly greater ROM from Control Group in the left shoulder joint flexion with a 5.82 mean difference. Swimmers have significantly higher ROM from the Control Group in the left shoulder joint flexion with 24.84 mean difference and swimmers have significantly higher ROM from the Middle and Long distance runners in left shoulder flexion with 19.02 mean difference. The picture will be clear after a more detailed investigation.

Keywords: range of motion, runners, swimmers, significance

Procedia PDF Downloads 124

Authors: Durata Haciu, Elif Sena Tekin, Gokce Ozturk, Patricia Ramey Balcı

Abstract:

Coastal zones are under increasing threat due to anthropogenic activities that introduce considerable pollutants such as heavy metals into marine ecosystems. As part of a larger experimental study examining species responses to contaminated marine sediments, surface sediments (top 5cm) were analysed for major trace elements at three locations in Istanbul Straight. Samples were randomly collected by divers (May 2018) using hand-corers from Istinye (n=4), Garipce (n=10) and Poyrazköy (n=6), at water depths of 4-8m. Twelve metals were examined: As, arsenic; Pb, lead; Cd, cadmium; Cr, chromium; Cu, Copper; Fe, Iron; Ni, Nickel; Zn, Zinc; V, vanadium; Mn, Manganese; Ba, Barium; and Ag, silver by wavelength-dispersive X-ray fluorescence spectrometry (WDXRF) and Inductively Coupled Plasma/Mass Spectroscopy (ICP/MS). Preliminary results indicate that the average concentrations of metals (mg kg⁻¹) varied considerably among locations. In general, concentrations were relatively lower at Garipce compared to either Istinye or Poyrazköy. For most metals mean concentrations were highest at Poyrazköy and Ag and Cd were below detection limits (exception= Ag in a few samples). While Cd and As were undetected in all stations, the concentrations of Fe and Ni fall in the criteria of moderately polluted range and the rest of the metals in the range of low polluted range as compared to Effects Range Low (ERL) and Effects Range median (ERM) values determined by US Environmental Protection Agency (EPA).

Keywords: effect-range classification, ICP/MS, marine sediments, XRF

Procedia PDF Downloads 129